Structural and cyclical determinants of access to finance: Evidence - - PowerPoint PPT Presentation

Structural and cyclical determinants of access to finance: Evidence from Egypt

Frank Betz1 Farshad Ravasan2 and Christoph Weiss1

1European Investment Bank 2Oxford University

20 January 2020

The research summarized in this presentation was supported by the EIB Institute through its STAREBEI programme.

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Why do we care?

Figure: Financially excluded firms remain small Figure: Egypt has many financially excluded firms

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Private sector credit in Egypt: from bad to worse

Figure: The government crowding out the private sector Figure: Public debt was partly monetized

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Why do firms participate in the financial system?

Egypt is know as a cash economy (94% of transactions in cash, according to Mastercard) and for its large informal sector Registered but unbanked forms operate on a semi-formal basis. This way

• f operating

may help firms to save on taxes but aggravates information asymmetries Operating on a informal (or semi-formal) basis can be optimal if intermediation capacity of the banking system is low (Straub, 2005) institutional quality is poor (Johnson et al., 2002)

• pportunity costs in the form of lost growth are low, for instance

because entrepreneurs are less skilled (Gennaioli et al., 2013)

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Results

Structural level Firms run by more experienced and more educated CEOs are more likely to become financially included over the sample period We do not find a role for intermediation capacity and institutional quality Entrepreneurial human capital appears to matter because of

• pportunity costs rather than financial literacy

Cyclical level CEO education and experience is positively associated with access to credit Crowding out reflected in greater prevalence of credit constraints

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This presentation

1

Motivation

2

Empirical strategy

3

Data

4

Results

5

Conclusion

6

Background slides

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Financial inclusion

To examine financial inclusion we estimate the following regression: ∆accounti = β1 ∗ crowdingouti + β2 ∗ ∆CEOeducationi + β3 ∗ ∆CEOexperiencei + γ ∗ Xi + Ui Where accounti equals 1 if the firm has a checking or savings account The ∆-prefix indicates the difference between the value in 2016 and 2013 (the two waves of the survey for Egypt) crowdingouti measures local supply of credit CEOeducationi is likely to change with CEO, thus all specifications also control for CEO experience.

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Credit constraints

To examine credit constraints we estimate the following regression: ∆constrainedi = β1 ∗ crowdingouti + β2 ∗ ∆CEOeducationi + β3 ∗ ∆CEOexperiencei + γ ∗ Xi + Ui Only firms that have demand for credit can be credit constrained. In a second step we use liquidity shocks to instrument credit demand. Candidate instruments: Loss due to spoilage Loss due to informal gift request Loss due to power outage Last step: Generalize to SN using 2013 cross-section of MENA ES

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Outline

1

Motivation

2

Empirical strategy

3

Data

4

Results

5

Conclusion

6

Background slides

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Firm-level data

Firm-level data come from the MENA Enterprise Survey The MENA ES is a representative firm-level survey financed jointly by EIB, EBRD, and the World Bank and conducted in 2013 The finance module of the survey asks firms whether they

have a checking or savings account are credit constrained (rejected or discouraged)

The survey also includes information on

firm characteristics educational attainment and experience of the manager business environment and institutional quality

In 2016, a follow-up survey was done in Egypt

longitudinal data (panel firms)

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Complementary data sources

The crowding-out index draws on information

• n the location of bank branches
• n bank security holdings and loans from Orbis BankFocus

and is computed as follows crowdingoutj =

2015

• t=2013

sj,t − lj,t

• j aj,t

−

2012

• t=2010

sj,t − lj,t

• j aj,t

where sj,t and lj,t denote security holdings and loans of bank j and

• j aj,t refers to total assets in the banking system.

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Bank balance sheets

Focus on the following banks: Public National Bank of Egypt Banque Misr Banque du Caire Private CIB Foreign QNB HSBC

Figure: Government debt mainly held by public banks

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Outline

1

Motivation

2

Empirical strategy

3

Data

4

Results

5

Conclusion

6

Background slides

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Financial inclusion: baseline results

(1) (2) (3) (4) ∆ Account ∆ Account ∆ Account ∆ Account ∆ CEO university education 0.127** 0.142** (0.06) (0.06) ∆ CEO experience 0.037* 0.047** (0.02) (0.02) ∆ CEO female

• 0.034
• 0.024

(0.08) (0.09) Initially informal

• 0.153**
• 0.170**
• 0.157**
• 0.168**

(0.07) (0.07) (0.07) (0.08) Young firm 0.182*** 0.164*** 0.167*** 0.175*** (0.06) (0.06) (0.06) (0.06) Small firm 0.124*** 0.136*** 0.129*** 0.130*** (0.05) (0.05) (0.05) (0.05) N 612 598 614 597 R2 0.06 0.06 0.05 0.07

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Financial inclusion and financial system characteristics

(1) (2) (3) (4) ∆ Account ∆ Account ∆ Account ∆ Account Local financial inclusion

• 0.087

(0.13) Local financial intermediation

• 0.064

(0.15) Crowding out index

• 0.030

(0.03) Liquidity shock 0.052 (0.05) ∆ CEO university education 0.124** 0.129** 0.104* 0.143** (0.06) (0.06) (0.06) (0.06) ∆ CEO experience 0.050** 0.052** 0.042* 0.045** (0.02) (0.02) (0.02) (0.02) ∆ CEO female

• 0.037
• 0.033
• 0.035
• 0.024

(0.09) (0.09) (0.09) (0.09) Initially informal

• 0.121
• 0.108
• 0.103
• 0.168**

(0.07) (0.10) (0.09) (0.09) N 545 545 516 597 R2 0.08 0.10 0.09 0.08

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Financial inclusion and institutional quality

(1) (2) (3) (4) ∆ Account ∆ Account ∆ Account ∆ Account ∆ political instability 0.064 (0.04) ∆ property rights enforced 0.005 (0.03) ∆ courts impartial

• 0.030

(0.03) ∆ courts quick

• 0.055

(0.04) ∆ CEO university education 0.135** 0.142** 0.140** 0.142** (0.06) (0.06) (0.06) (0.06) ∆ CEO experience 0.045** 0.047** 0.048** 0.047** (0.02) (0.02) (0.02) (0.02) ∆ CEO female

• 0.019
• 0.024
• 0.022
• 0.015

(0.08) (0.09) (0.09) (0.09) Initially informal

• 0.174**
• 0.168**
• 0.174**
• 0.168**

(0.07) (0.08) (0.08) (0.08) Sample size 590 597 597 597 R2 0.08 0.07 0.08 0.08

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Credit constraints

(1) (2) (3) (4) ∆ constrained ∆ discouraged ∆ rejected ∆ constrained Crowding out index 0.065** 0.062** 0.004 0.052* (0.03) (0.03) (0.01) (0.03) ∆ CEO university education

• 0.115*
• 0.154**

0.038**

• 0.097

(0.06) (0.06) (0.02) (0.06) ∆ CEO experience

• 0.014
• 0.035

0.021**

• 0.011

(0.02) (0.02) (0.01) (0.02) ∆ CEO female

• 0.095
• 0.102

0.007

• 0.098

(0.09) (0.09) (0.01) (0.09) ∆ ownership 0.187** 0.190***

• 0.002

0.203*** (0.07) (0.07) (0.01) (0.08) ∆ exporter 0.169*** 0.147** 0.022 0.196*** (0.06) (0.06) (0.02) (0.06) ∆ audit

• 0.068
• 0.059
• 0.009
• 0.051

(0.04) (0.04) (0.01) (0.05) Initially informal 0.223** 0.186* 0.037 0.214* (0.11) (0.11) (0.03) (0.11) ∆ account

• 0.104**

(0.05) N 521 521 521 516 R2 0.10 0.10 0.06 0.11 Access to finance 20 January 2020 17 / 28

Instrumenting credit demand

(1) (2) (3) (4) ∆ need ∆ constrained ∆ discouraged ∆ rejected Liquidity shock 0.213*** (0.06) Crowding out index 0.022 0.043*** 0.040** 0.003 (0.03) (0.02) (0.02) (0.01) ∆ CEO university education

• 0.083
• 0.052**
• 0.092***

0.040** (0.06) (0.03) (0.03) (0.02) ∆ CEO experience

• 0.002
• 0.018
• 0.038***

0.020** (0.02) (0.01) (0.01) (0.01) ∆ CEO female

• 0.154

0.023 0.013 0.010 (0.09) (0.07) (0.07) (0.02) ∆ ownership 0.222**

• 0.003

0.003

• 0.006

(0.09) (0.06) (0.06) (0.02) ∆ exporter 0.232***

• 0.006
• 0.025

0.018 (0.07) (0.05) (0.05) (0.02) ∆ audit

• 0.067
• 0.023
• 0.015
• 0.008

(0.05) (0.02) (0.03) (0.01) Initially informal 0.225** 0.056 0.023 0.034 (0.10) (0.07) (0.07) (0.03) ∆ need 0.742*** 0.726*** 0.016 (0.15) (0.16) (0.08) N 521 521 521 521 R2 0.74 0.71 0.07 Access to finance 20 January 2020 18 / 28

Financial literacy and firm quality

(1) (2) (3) (4) ∆ Procedures ∆ Website ∆ Innovator ∆ Expansion ∆ CEO university education 0.004 0.086** 0.076* 0.153** (0.04) (0.04) (0.04) (0.07) ∆ CEO experience

• 0.012

0.007 0.014 0.025 (0.02) (0.02) (0.02) (0.03) ∆ CEO female 0.004 0.098 0.142

• 0.067

(0.06) (0.07) (0.09) (0.17) Initially informal 0.160***

• 0.055

0.021 0.066 (0.06) (0.07) (0.07) (0.12) Young firm

• 0.013

0.176*** 0.026 0.116 (0.04) (0.06) (0.06) (0.08) Small firm 0.045 0.029 0.057

• 0.095

(0.03) (0.05) (0.04) (0.07) N 603 601 603 291 R2 0.04 0.05 0.05 0.10 Access to finance 20 January 2020 19 / 28

Regional results: financial inclusion

(1) (2) (3) (4) ∆ Account ∆ Account ∆ Account ∆ Account CEO university education 0.063*** 0.063*** (0.01) (0.01) CEO experience 0.000 0.005 (0.01) (0.01) CEO female 0.010 0.001 (0.02) (0.02) Initially informal

• 0.094***
• 0.090***
• 0.106***
• 0.079***

(0.03) (0.03) (0.03) (0.03) N 2285 2235 2285 2235 R2 0.12 0.11 0.11 0.12

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Regional results: credit constraints

(1) (2) (3) (4) Need Constrained Discouraged Rejected CEO university education

• 0.043
• 0.126***
• 0.123***
• 0.004

(0.06) (0.03) (0.04) (0.01) CEO experience

• 0.039
• 0.051***
• 0.053***

0.002 (0.03) (0.02) (0.02) (0.01) CEO female 0.204

• 0.007
• 0.005
• 0.001

(0.14) (0.07) (0.08) (0.03) Crowding out index 0.095*

• 0.020
• 0.008
• 0.011

(0.05) (0.04) (0.04) (0.02) Foreign ownership

• 0.384***
• 0.014
• 0.010
• 0.004

(0.11) (0.09) (0.09) (0.04) Exporter

• 0.038
• 0.011
• 0.025

0.014 (0.07) (0.04) (0.04) (0.01) Audit 0.139**

• 0.139***
• 0.144***

0.005 (0.07) (0.04) (0.05) (0.02) Initially informal

• 0.028

0.031

• 0.017

0.048** (0.10) (0.06) (0.06) (0.02) N 2167 2167 2167 2167

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Outline

1

Motivation

2

Empirical strategy

3

Data

4

Results

5

Conclusion

6

Background slides

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Conclusion

Structural level Firms run by more experienced and more educated CEOs are more likely to become financially included over the sample period We do not find a role for intermediation capacity and institutional quality Entrepreneurial human capital appears to matter because of

• pportunity costs rather than financial literacy

Implies that business environment reform can also be conducive to financial inclusion Cyclical level CEO education and experience is positively associated with access to credit Crowding out reflected in greater prevalence of credit constraints

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Outline

1

Motivation

2

Empirical strategy

3

Data

4

Results

5

Conclusion

6

Background slides

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The costs and benefits of operating formally

When deciding whether to register, firms trade-off the costs and benefits

• f operating formally, where costs are given by

taxes regulations and benefits come from access to the judiciary financial system We do not have data on unregistered firms but think of unbanked firms as

• perating on a semi-formal basis.

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Implications

Operating on a cash-only basis helps firms to save on taxes aggravates information asymmetries The SME lending programme proposed by Munro (2013) demands that small firms without financial statements run their activities through a checking account for one year to establish a reliable sales figure. Therefore, firms are more likely to operate on a semi-formal basis if intermediation capacity of the banking system is low (Straub, 2005)

• pportunity costs in the form of lost growth is low

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Opportunity costs

Entrepreurial human capital and financial literacy La Porta and Shleifer (2014) find that informal firms tend to be small and unproductive. They argue that the low levels of productivity reflect lack of skills on the side of the entrepreneurs. Gennaioli et al (2013) document a strong association between entrepreneurial human capital and firm productivity. Institutions Acemoglu et al (2001) argue that secure property rights are a determinant of economic growth. If entrepreneurs cannot reap the reward for their efforts they will not invest in the first place. Using data from five Eastern European countries Johnson et al (2002) find that the perceived strength of property rights affects the willingness of entrepreneurs to reinvest their profits.

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Spatial distribution of firms and bank branches

(a) Sample firms (b) Public banks (c) Private banks (d) Foreign banks

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Comments on: Structural and cyclical determinants of access to finance: Evidence from Egypt Betz, Ravasan & Weiss (2019)

Discussant: Cristian Rojas Financial Market Commission First Conference on Financial Stability and Sustainability January 20th and 21st, 2020 Universidad del Pacífico (Lima, Perú)

Contents

• This paper contributes to the literature with new results about the

relationship between firms and credit markets, in terms of institutional variables.

• It employs panel data models studying firms’ financing access.
• The main results are:

1. Firms run by CEOs with a higher level of education and experience are more likely to be banked and more likely to have access to credit. 2. Firms that in the past where informal are less likely to be banked when they become formal. 3. Firms more exposed to a crowding-out effect (surrounded by banks branches that invest more in government debt) will be more credit constrained.

2

Areas for improvement

• First: Conceptual framework.
• Second: Relationship between the variables.
• Third: Review the comparison with other countries.

3

Areas for improvement

1) Conceptual framework

• In general, the paper discusses “institutional determinants” of access to credit.
• But It is not clear enough the conceptual framework of being constrained and

having a bank account.

• Egypt is a particular country: is an emerging market but with a lot of informality

¿To which type of countries we could expect to interpolate the results?

4

Areas for improvement

2) Relationship between the variables

• There would be interesting to study the interaction of some of the variables.
• For example, established if having a CEO with a high level of education can
• vercome the credit restrain in firms exposed to a crowding-out effects.
• What role plays the size of the firms? Is it possible to split SMEs from big

companies?

• Studies like Distinguin et al (2016) find that for SME the competition with

informal are relevant in terms of credit restraint.

5

Areas for improvement

3) Review the comparison with other countries

• The comparison with other countries is not fully equivalent. Is this section a

robustness section?

6

Final remarks

• It is an interesting paper that describes how institutional variables

determine the probability of having a banking account and be credit restraint.

• Very critical topic for small firms and firms in Emerging Markets.
• Microdata analysis based on panel data models is a plus.
• A further analysis of the credit demand could be more studied.

7

Comments on: Structural and cyclical determinants of access to finance: Evidence from Egypt Betz, Ravasan & Weiss (2019)

Discussant: Cristian Rojas Financial Market Commission First Conference on Financial Stability and Sustainability January 20th and 21st, 2020 Universidad del Pacífico (Lima, Perú)